Udemy – DSP From Ground Up™ on ARM Processors [UPDATED]

Do you want to learn practical digital signal processing (dsp) without confusion? Here’s an overview of what you’re getting in this dsp on Arm processors course…

Understanding the foundations of signal processing without complications:

Before going on to implement practical dsp algorithms from scratch, this course teaches you the foundation of signal processing step-by-step. We shall look at key topics in signal processing including:

• Signal statistics and noise
• Quantization and sampling theorem
• Analog filter design
• Performance metrics of the Chebyshev, Butterworth, and Bessel filters
• Linear systems and their properties.
• Finite Impulse Response Filters (FIR)
• Infinite Impulse Response Filters (IIR)
• Superposition, synthesis, and decomposition.
• Convolution and its properties
• Discrete Fourier Transform (DFT) and IDFT

Developing Digital Signal Processing Algorithms:

We shall practically develop the signal processing algorithms we discussed in the theory class. Over here rather than use live signals we shall use some already acquired and generated signals to test our algorithms, to keep the focus on developing the algorithms and testing them, rather than signal acquisition.

We shall develop the following algorithms:

• Signal statistics algorithms: signal mean, signal standard deviation, signal variance
• The Convolution algorithm
• The Running Sum algorithm
• The Discrete Fourier Transform (DFT) algorithm
• The Inverse Discrete Fourier Transform (IDFT) algorithm

We shall also implement some of these algorithms using the CMSIS-DSP library and then compare the dynamic performance     of our algorithm to that of the ones provided by CMSIS-DSP.